The project was started as a reaction to the spreading of data across “relational databases, non-relational data stores, and data lakes” companies see today. Since most data stores come with their own query language, transforming data and moving it to another platform can get quite complicated and may require changes in applications and queries.
With the amount of tabular, nested, and semi-structured data that can be found across Amazon’s retail business and AWS services, the company needed a way to solve those issues and started work on PartiQL. The language’s design goals included SQL compatibility to keep SQL queries intact, first-class support for nested data, optional schema and query stability, minimal extensions over SQL, format independence, and data store independence as key development goals.
The now released outcome separates a query’s syntax and semantics from the data source and format, so that users can query data no matter how or where they are stored. A first reference implementation written in Kotlin, JetBrains’ language for the JVM, a specification document, and a PartiQL tutorial are available now under the Apache 2 license.